654 research outputs found

    Safety profile of oxcarbazepine: results from a prescription-event monitoring study

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    Purpose: To monitor safety of oxcarbazepine, prescribed in primary care in England, using prescription-event monitoring (PEM). Methods: Postmarketing surveillance using observational cohort technique of PEM. Exposure data were obtained from dispensed British National Health Service prescriptions issued by general practitioners (GPs) March 2000–July 2003. Demographic, drug utilization, and clinical event data were collected from questionnaires posted to GPs at least 6 months after first prescription date for each patient. Incidence densities (IDs) (number of first reports per 1,000 patient-months of treatment) were calculated and differences for events reported in month 1 (ID1) and months 2–6 (ID2–6) (99% confidence intervals) were examined for changes in event rates. Follow-up and causality assessment of medically significant events were undertaken. Results: The cohort comprised 2,243 patients [mean age 40.4 years; range 2–99 years; standard deviation (SD) 18.8; 46.3% (n = 1,038) male]. Most frequently reported primary indications were epilepsy, convulsion (n = 1,111; 49.5%, n = 209; 9.3%, respectively). GPs recorded 932 reasons for stopping medication in 698 (31.1%) patients; most frequent clinical reason “drowsiness/sedation” (n = 57; 2.5% of cohort). Clinical events (excluding indication) associated with starting treatment (lower 99% CI > 0) included: “drowsiness/sedation” (ID1-ID2–6 = 14.2), “nausea/vomiting” (ID1-ID2–6 = 13.0), and dizziness (ID1-ID2–6 = 11.6). Events followed up and assessed as probably related to oxcarbazepine use included rash (7 of 11) and hyponatremia (15 of 38). Discussion:  There were no serious adverse drug reactions reported during this study. Results of the study should be taken in context with other epidemiologic studies

    Numerical analysis of the Taylor Galerkin Pressure Correction (TGPC) finite element method for Newtonian fluid

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    In this study, a time stepping Taylor Galerkin Pressure Correction finite element scheme (TGPC) is investigated on the basis of incompressible Newtonian flows. Naiver-Stoke partial differential equations have been used to describe the motion of the fluid. The equations consist of a time-dependent continuity equation for conservation of mass and time-dependent conservation of momentum equations. Examples considered include a start-up of Poiseuille flow in a rectangular channel for the Newtonian fluid. In that context, three different meshes 2×2, 5×5 and 10×10 are implemented to investigate the effect mesh refinements on the accuracy of the solution. In addition, the behaviour of velocity and pressure are reported in this study. Keywords: Finite element methods, Taylor expansion, Naiver-Stoke equations, Newtonian fluid, Galerkin metho

    Special Section: Signal Processing for Large Scale 5G Wireless Networks

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    Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction

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    PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) is a recent imaging modality that allows performing in vivo optical biopsies. The design of pCLE hardware, and its reliance on an optical fibre bundle, fundamentally limits the image quality with a few tens of thousands fibres, each acting as the equivalent of a single-pixel detector, assembled into a single fibre bundle. Video registration techniques can be used to estimate high-resolution (HR) images by exploiting the temporal information contained in a sequence of low-resolution (LR) images. However, the alignment of LR frames, required for the fusion, is computationally demanding and prone to artefacts. METHODS: In this work, we propose a novel synthetic data generation approach to train exemplar-based Deep Neural Networks (DNNs). HR pCLE images with enhanced quality are recovered by the models trained on pairs of estimated HR images (generated by the video registration algorithm) and realistic synthetic LR images. Performance of three different state-of-the-art DNNs techniques were analysed on a Smart Atlas database of 8806 images from 238 pCLE video sequences. The results were validated through an extensive image quality assessment that takes into account different quality scores, including a Mean Opinion Score (MOS). RESULTS: Results indicate that the proposed solution produces an effective improvement in the quality of the obtained reconstructed image. CONCLUSION: The proposed training strategy and associated DNNs allows us to perform convincing super-resolution of pCLE images

    Drugs and life-threatening ventricular arrhythmia risk: results from the DARE study cohort.

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    OBJECTIVES: To establish a unique sample of proarrhythmia cases, determine the characteristics of cases and estimate the contribution of individual drugs to the incidence of proarrhythmia within these cases. SETTING: Suspected proarrhythmia cases were referred by cardiologists across England between 2003 and 2011. Information on demography, symptoms, prior medical and drug histories and data from hospital notes were collected. PARTICIPANTS: Two expert cardiologists reviewed data for 293 referred cases: 130 were included. Inclusion criteria were new onset or exacerbation of pre-existing ventricular arrhythmias, QTc >500 ms, QTc >450 ms (men) or >470 ms (women) with cardiac syncope, all secondary to drug administration. Exclusion criteria were acute ischaemia and ischaemic polymorphic ventricular tachycardia at presentation, structural heart disease, consent withdrawn or deceased prior to study. Descriptive analysis of Caucasian cases (95% of included cases, n=124) and culpable drug exposures was performed. RESULTS: Of the 124 Caucasian cases, 95 (77%) were QTc interval prolongation-related; mean age was 62 years (SD 15), and 63% were female. Cardiovascular comorbidities included hypertension (53%) and patient-reported 'heart rhythm problems' (73%). Family history of sudden death (36%) and hypokalaemia at presentation (27%) were common. 165 culpable drug exposures were reported, including antiarrhythmics (42%), of which amiodarone and flecainide were the most common. Sotalol, a beta-blocking agent with antiarrhythmic activity, was also common (15%). 26% reported multiple drugs, of which 84% reported at least one cytochrome (CYP) P450 inhibitor. Potential pharmacodynamics interactions identified were mainly QT prolongation (59%). CONCLUSIONS: Antiarrhythmics, non-cardiac drugs and drug combinations were found to be culpable in a large cohort of 124 clinically validated proarrhythmia cases. Potential clinical factors that may warn the prescriber of potential proarrhythmia include older women, underlying cardiovascular comorbidity, family history of sudden death and hypokalaemia

    Learning from irregularly sampled data for endomicroscopy super-resolution: a comparative study of sparse and dense approaches

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    PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) enables performing an optical biopsy via a probe. pCLE probes consist of multiple optical fibres arranged in a bundle, which taken together generate signals in an irregularly sampled pattern. Current pCLE reconstruction is based on interpolating irregular signals onto an over-sampled Cartesian grid, using a naive linear interpolation. It was shown that convolutional neural networks (CNNs) could improve pCLE image quality. Yet classical CNNs may be suboptimal in regard to irregular data. METHODS: We compare pCLE reconstruction and super-resolution (SR) methods taking irregularly sampled or reconstructed pCLE images as input. We also propose to embed a Nadaraya-Watson (NW) kernel regression into the CNN framework as a novel trainable CNN layer. We design deep learning architectures allowing for reconstructing high-quality pCLE images directly from the irregularly sampled input data. We created synthetic sparse pCLE images to evaluate our methodology. RESULTS: The results were validated through an image quality assessment based on a combination of the following metrics: peak signal-to-noise ratio and the structural similarity index. Our analysis indicates that both dense and sparse CNNs outperform the reconstruction method currently used in the clinic. CONCLUSION: The main contributions of our study are a comparison of sparse and dense approach in pCLE image reconstruction. We also implement trainable generalised NW kernel regression as a novel sparse approach. We also generated synthetic data for training pCLE SR

    User equipment geolocation depended on long-term evolution signal-level measurements and timing advance

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    A new approach is described for investigating the accuracy of positioning active long-term evolution (LTE) users. The explored approach is a network-based method and depends on signal level measurements as well as the coverage of the serving cell. In a two-dimensional coordinate system, the algorithm simultaneously applies LTE measured data with a combination of a basic prediction model to locate the mobile device’s user. Furthermore, we introduce a unique method that combines timing advance (TA) and the measured signal level to narrow the search region and improve accuracy. The developed method is assessed by comparing the predicted results from the proposed algorithm with satellite measurements from the global positioning system (GPS) in various scenarios calculated via the number of cells that user equipment concurrently reports. This work separates seven different cases starting from a single reported cell to five reported cells from up to 3 sites. For analysis, the root mean square error (RMSE) is computed to obtain the validation for the proposed approach. The study case demonstrates location accuracy based on the numbers of registered cells with the mean RMSE improved using TA to approximately 70-191 m for the range of scenarios

    Synaptic Interactions in Scorpion Peg Sensilla Appear to Maintain Chemosensory Neurons within Dynamic Firing Range

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    Scorpions have elaborate chemo-tactile organs called pectines on their ventral mesosoma. The teeth of the comb-like pectines support thousands of minute projections called peg sensilla (a.k.a. “pegs”), each containing approximately 10 chemosensory neurons. Males use pectines to detect pheromones released by females, and both sexes apparently use pectines to find prey and navigate to home retreats. Electrophysiological recordings from pegs of Paruroctonus utahensis reveal three spontaneously active cells (A1, A2, and B), which appear to interact synaptically. We made long-term extracellular recordings from the bases of peg sensilla and used a combination of conditional cross-interval and conditional interspike-interval analyses to assess the temporal dynamics of the A and B spike trains. Like previous studies, we found that A cells are inhibited by B cells for tens of milliseconds. However, after normalizing our records, we also found clear evidence that the A cells excite the B cells. This simple local circuit appears to maintain the A cells in a dynamic firing range and may have important implications for tracking pheromonal trails and sensing substrate chemistry for navigation.Open Access fees paid for in whole or in part by the University of Oklahoma Libraries.Ye

    Rutin Attenuates Hepatotoxicity in High-Cholesterol-Diet-Fed Rats

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    Background and Objective. High-cholesterol diet (HCD) intends to increase the oxidative stress in liver tissues inducing hepatotoxicity. Rutin is a natural flavonoid (vitamin p) which is known to have antioxidative properties. The aim of the present study was to investigate the potential effects of Rutin on hypercholesterolemia-induced hepatotoxicity in rats. Materials and Methods. Male Wistar rats were divided into four groups: G-I control, G-II Rutin, G-III HCD, and G-IV Rutin + HCD. The liver functions and lipid profile were used to evaluate the HCD-induced hepatotoxicity. Quantitative real time-PCR was carried out to evaluate the expression levels of genes in TGF-β/Smad signaling pathway. Results. Rutin in combination with HCD showed a significant protective effect against hepatotoxicity. HCD caused significant increase in the mRNA expression of transforming growth factor beta (TGF-β), Mothers Against Decapentaplegic Homolog 2 (Smad-2), Mothers Against Decapentaplegic Homolog 4 (Smad-4), Bcl-2-binding component 3 (Bbc3), caspase-3, P53 and Interleukin-6 (IL-6) and decrease in the expression levels of Cyclin depended kinase inhibitor (P21) and Interleukin-3 (IL-3) in hepatic cells. Conclusion. TGF-β/Smad signaling pathway is involved in HCD-induced hepatotoxicity and Rutin inhibits the hepatotoxicity via suppressing this pathway. Therefore, Rutin might be considered as a protective agent for hepatotoxicity

    A Combined EM and Visual Tracking Probabilistic Model for Robust Mosaicking: Application to Fetoscopy

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    Twin-to-Twin Transfusion Syndrome (TTTS) is a progressive pregnancy complication in which inter-twin vascular connections in the shared placenta result in a blood flow imbalance between the twins. The most effective therapy is to sever these connections by laser photo-coagulation. However, the limited field of view of the fetoscope hinders their identification. A potential solution is to augment the surgeon’s view by creating a mosaic image of the placenta. State-of-the-art mosaicking methods use feature-based ap- proaches, which have three main limitations: (i) they are not robust against corrupt data e.g. blurred frames, (ii) tem- poral information is not used, (iii) the resulting mosaic suf- fers from drift. We introduce a probabilistic temporal model that incorporates electromagnetic and visual tracking data to achieve a robust mosaic with reduced drift. By assuming planarity of the imaged object, the nRT decomposition can be used to parametrize the state vector. Finally, we tackle the non-linear nature of the problem in a numerically stable manner by using the Square Root Unscented Kalman Filter. We show an improvement in performance in terms of robustness as well as a reduction of the drift in comparison to state-of-the-art methods in synthetic, phantom and ex vivo datasets
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